The pathology in peripheral arterial disease (PAD) may be multifactorial, including both a perfusion deficit and metabolic/structural changes in the skeletal muscle. Yet conventional approaches to analyzing PAD may have analyzed single factors at a time. Diagnosing PAD, tracking the progression of PAD, tracking the efficacy of a treatment for PAD, or other perfusion related analysis have been limited by single factor approaches. When performing a liver or kidney transplant, understanding the location, health, function, and other information about vasculature associated with the organ may be essential to a successful procedure. Conventional imaging approaches to understanding pre-surgical arterial information may also have been analyzed using a single factor at a time. When performing a resection of a tumor in, for example, a kidney or liver, understanding the location, health, function, and other information about how the tumor is vascularized may be important to a successful procedure. Yet once again, conventional imaging approaches may have analyzed a single factor at a time. Similarly, when preparing for brain surgery (e.g., implanting deep brain stimulation electrode, resecting tumor), understanding the location, health, function, and other information about how the relevant region is vascularized may be important to a successful procedure.
Vascular pathologies can affect large and small vessels, and can manifest as perfusion deficits from downstream effects of large vessel disease or directly from small vessel disease. Comprehensive vascular evaluation may be improved by assessing both large and small vessels. Magnetic resonance angiography (MRA) has been used to image large arteries to, for example, assess arterial pathology. While MRA is useful for large vessels, MRA is less useful for the microvasculature. Therefore, dynamic contrast-enhanced (DCE) techniques for acquiring quantitative perfusion maps have been applied to analyze the microvasculature. Conventional approaches may have performed a pharmacokinetic analysis of an administered contrast agent (e.g., Gadolinium). Conventionally, magnetic resonance imaging (MRI) based DCE perfusion and MRA have been be used to separately assess the macro- and microvasculature. Since MRA and perfusion exams have conventionally used a separate, full-dose (as calculated by patient weight) contrast bolus, the two studies have conventionally been performed on different days to avoid contamination of the second exam and contrast double-dosing. These factors have effectively precluded the use of MRI to evaluate both micro-vascular and macro-vascular components of disease simultaneously. Thus, the multifactorial etiologies of vascular pathologies such as PAD may have been incompletely explored.
Time-resolved MRA (trMRA) techniques have been performed by acquiring three dimensional (3D) images at several points in time to dynamically visualize arterial anatomy at different phases of contrast agent arrival. These images may have contained high spatial resolution data concerning large vessels. The data on the large vessels may have included some embedded tissue enhancement information. However, trMRA image acquisitions are optimized for visualizing vascular anatomy and not DCE analysis. Thus, MRA and Perfusion (MRAP) provided a simultaneous approach that maintained the high spatial resolution needed to visualize the vasculature while also achieving high temporal resolution and sufficient tissue signal-to-noise ratio (SNR) to accurately capture changes in contrast agent concentration used in estimating perfusion. By simultaneously acquiring angiography images and calculating quantitative perfusion parameters, MRAP accomplished both small and large vessel assessment in a single exam and contrast dose. However, in conventional MRAP, MRI relaxation parameters (e.g., T1, T2) may only have been available as crude baseline measures. Conventional MRAP is described in Simultaneous Magnetic Resonance Angiography And Perfusion (MRAP) Measurement: Initial Application in Lower Extremity Skeletal Muscle, Wright et al., JOURNAL OF MAGNETIC RESONANCE IMAGING 38:1237-1244 (2013), which is incorporated herein in its entirety.
Conventional magnetic resonance (MR) pulse sequences included a preparation phase, a waiting phase, and an acquisition phase that serially produced signals from which images could be made serially. The preparation phase determined when a signal could be acquired and determined the properties of the acquired signal. For example, a first pulse sequence may have been designed to produce a T1-weighted signal at a first echo time (TE) while a second pulse sequence may have been designed to produce a T2-weighted signal at a second TE. These conventional pulse sequences were typically designed to provide qualitative results where data were acquired with various weightings or contrasts that highlighted a particular parameter (e.g., T1 relaxation, T2 relaxation).
When MR images were generated, they may have been viewed by a radiologist and/or surgeon who interpreted the qualitative images for specific disease signatures. The radiologist may have examined multiple image types (e.g., T1-weighted, T2-weighted) acquired in multiple imaging planes to make a diagnosis. The radiologist or other individual examining the qualitative images may have needed particular skill to be able to assess changes from session to session, from machine to machine, and from machine configuration to machine configuration. Thus, the qualitative images were only as good as the image interpreter and all image based (e.g., qualitative) diagnoses ended up being subjective.
Magnetic resonance fingerprinting (MRF) employed a series of varied sequence blocks that simultaneously produced different signal evolutions in different resonant species (e.g., tissues) to which the radio frequency (RF) in an MR pulse sequence was applied. The term “resonant species”, as used herein, refers to an item (e.g., water, fat, tissue, material) that can be made to resonate using nuclear magnetic resonance (NMR). By way of illustration, when example apparatus and methods apply RF energy to a volume that has both bone and muscle tissue, then both the bone and muscle tissue will produce an NMR signal. However the “bone signal” and the “muscle signal” will be different. The different signals can be collected over a period of time to identify a signal evolution for the volume. Resonant species in the volume can then be characterized by comparing the signal evolution to known evolutions.
Conventional MRF may access a large set of known evolutions in a dictionary. Characterizing the resonant species can include identifying different properties of a resonant species (e.g., T1, T2, diffusion resonant frequency, diffusion co-efficient, spin density, proton density). Additionally, other properties including, but not limited to, tissue types, materials, and super-position of attributes (e.g., T1, T2) can be identified.
MRF is described in United States Patent Application “Nuclear Magnetic Resonance (NMR) Fingerprinting”, application Ser. No. 13/051,044, and in Magnetic Resonance Fingerprinting, Ma et al., Nature 495, 187-192 (14 Mar. 2013), the contents of both of which are incorporated herein by reference.